71 lines
2.7 KiB
Markdown
71 lines
2.7 KiB
Markdown
|
---
|
|||
|
|
license: llama2
|
|||
|
|
tags:
|
|||
|
|
- text2text-generation
|
|||
|
|
pipeline_tag: text2text-generation
|
|||
|
|
language:
|
|||
|
|
- zh
|
|||
|
|
- en
|
|||
|
|
---
|
|||
|
|
|
|||
|
|
# Model Card for Model ID
|
|||
|
|
|
|||
|
|
## Welcome
|
|||
|
|
If you find this model helpful, please *like* this model and star us on https://github.com/LianjiaTech/BELLE !
|
|||
|
|
|
|||
|
|
## Model description
|
|||
|
|
This model is obtained by fine-tuning the complete parameters using 0.4M Chinese instruction data on the original Llama2-13B-chat.
|
|||
|
|
We firmly believe that the original Llama2-chat exhibits commendable performance post Supervised Fine-Tuning (SFT) and Reinforcement Learning with Human Feedback (RLHF).
|
|||
|
|
Our pursuit continues to be the further enhancement of this model using Chinese instructional data for fine-tuning, with an aspiration to facilitate stable and high-quality
|
|||
|
|
Chinese language outputs.
|
|||
|
|
## Use model
|
|||
|
|
Please note that the input should be formatted as follows in both **training** and **inference**.
|
|||
|
|
``` python
|
|||
|
|
Human: \n{input}\n\nAssistant:\n
|
|||
|
|
```
|
|||
|
|
|
|||
|
|
|
|||
|
|
After you decrypt the files, BELLE-Llama2-13B-chat-0.4M can be easily loaded with AutoModelForCausalLM.
|
|||
|
|
``` python
|
|||
|
|
from transformers import AutoModelForCausalLM, LlamaTokenizer
|
|||
|
|
import torch
|
|||
|
|
|
|||
|
|
ckpt = '/path/to_finetuned_model/'
|
|||
|
|
device = torch.device('cuda')
|
|||
|
|
model = AutoModelForCausalLM.from_pretrained(ckpt).half().to(device)
|
|||
|
|
tokenizer = LlamaTokenizer.from_pretrained(ckpt)
|
|||
|
|
prompt = "Human: \n写一首中文歌曲，赞美大自然 \n\nAssistant: \n"
|
|||
|
|
input_ids = tokenizer(prompt, return_tensors="pt").input_ids.to(device)
|
|||
|
|
generate_ids = model.generate(input_ids, max_new_tokens=1024, do_sample=True, top_k=30, top_p=0.85, temperature=0.5, repetition_penalty=1.2, eos_token_id=2, bos_token_id=1, pad_token_id=0)
|
|||
|
|
output = tokenizer.batch_decode(generate_ids, skip_special_tokens=True, clean_up_tokenization_spaces=False)[0]
|
|||
|
|
response = output[len(prompt):]
|
|||
|
|
print(response)
|
|||
|
|
|
|||
|
|
```
|
|||
|
|
|
|||
|
|
|
|||
|
|
## Limitations
|
|||
|
|
There still exists a few issues in the model trained on current base model and data:
|
|||
|
|
|
|||
|
|
1. The model might generate factual errors when asked to follow instructions related to facts.
|
|||
|
|
|
|||
|
|
2. Occasionally generates harmful responses since the model still struggles to identify potential harmful instructions.
|
|||
|
|
|
|||
|
|
3. Needs improvements on reasoning and coding.
|
|||
|
|
|
|||
|
|
Since the model still has its limitations, we require developers only use the open-sourced code, data, model and any other artifacts generated via this project for research purposes. Commercial use and other potential harmful use cases are not allowed.
|
|||
|
|
|
|||
|
|
## Citation
|
|||
|
|
|
|||
|
|
Please cite our paper and github when using our code, data or model.
|
|||
|
|
|
|||
|
|
```
|
|||
|
|
@misc{BELLE,
|
|||
|
|
author = {BELLEGroup},
|
|||
|
|
title = {BELLE: Be Everyone's Large Language model Engine},
|
|||
|
|
year = {2023},
|
|||
|
|
publisher = {GitHub},
|
|||
|
|
journal = {GitHub repository},
|
|||
|
|
howpublished = {\url{https://github.com/LianjiaTech/BELLE}},
|
|||
|
|
}
|
|||
|
|
```
|